Title: 'MGMS2' for Polymicrobial Samples
Version: 1.0.2
Author: So Young Ryu ORCID iD [aut], George Wendt ORCID iD [cre]
Maintainer: George Wendt <gwendt@unr.edu>
Description: A glycolipid mass spectrometry technology has the potential to accurately identify individual bacterial species from polymicrobial samples. To develop bacterial identification algorithms (e.g. machine learning) using this glycolipid technology, it is necessary to generate a large number of various in-silico polymicrobial mass spectra that are similar to real mass spectra. 'MGMS2' (Membrane Glycolipid Mass Spectrum Simulator) generates such in-silico mass spectra, considering errors in m/z (mass-to-charge ratio) and variances of intensity values, occasions of missing signature ions, and noise peaks. It estimates summary statistics of monomicrobial mass spectra for each strain or species and simulates polymicrobial glycolipid mass spectra using the summary statistics of monomicrobial mass spectra. References: Ryu, S.Y., Wendt, G.A., Chandler, C.E., Ernst, R.K. and Goodlett, D.R. (2019) <doi:10.1021/acs.analchem.9b03340> "Model-based Spectral Library Approach for Bacterial Identification via Membrane Glycolipids." Gibb, S. and Strimmer, K. (2012) <doi:10.1093/bioinformatics/bts447> "MALDIquant: a versatile R package for the analysis of mass spectrometry data."
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: MALDIquant, MALDIquantForeign
RoxygenNote: 7.0.2
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-04-23 23:25:21 UTC; jakewendt
Repository: CRAN
Date/Publication: 2020-04-24 04:10:02 UTC

characterize_peak

Description

This function characterizes peaks by species/strain in a simulated spectrum after taking the highest peak or merging peaks in each bin.

Usage

characterize_peak(spec, option = 1, bin.size = 1, min.mz = 1000, max.mz = 2200)

Arguments

spec

A data frame that contains m/z values of peaks, normalized intensities of peaks, species names, and strain names. Either an output of simulate_poly_spectra or one elements of a list output from simulate_many_poly_spectra.

option

An option on how to merge peaks. There are two options: 1) no merge, thus take the highest intensity peak in each bin after binning a spectrum by bin.size, or 2) take a sum of intensity within each bin after binning a spectrum by bin.size.

bin.size

An integer. A bin size. (1 by default)

min.mz

A real number. Minimum mass-to-charge ratio. (1000 by default)

max.mz

A real number. Maximum mass-to-charge ratio. (2200 by default)

Value

A data frame that contains m/z values of peaks (mz), intensities of peaks (int), species names (species), and strain names (strain). Species and strain columns may contain more than one species/strain if an option 2 is chosen.

Examples

spectra.processed.A <- process_monospectra(
   file=system.file("extdata", "listA.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.B <- process_monospectra(
   file=system.file("extdata", "listB.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.C <- process_monospectra(
   file=system.file("extdata", "listC.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.mono.summary.A <- summarize_monospectra(
   processed.obj=spectra.processed.A,
   species='A', directory=tempdir())
spectra.mono.summary.B <- summarize_monospectra(
   processed.obj=spectra.processed.B,
   species='B', directory=tempdir())
spectra.mono.summary.C <- summarize_monospectra(
   processed.obj=spectra.processed.C,
   species='C', directory=tempdir())
mono.info=gather_summary(c(spectra.mono.summary.A, spectra.mono.summary.B, spectra.mono.summary.C))
mixture.ratio <- list()
mixture.ratio['A']=1
mixture.ratio['B']=0.5
mixture.ratio['C']=0
sim.template <- create_insilico_mixture_template(mono.info)
insilico.spectrum <- simulate_poly_spectra(sim.template, mixture.ratio)
merged.spectrum <- characterize_peak(insilico.spectrum, option=2)

create_insilico_mixture_template

Description

This function generates an intial template for simulated mass spectra.

Usage

create_insilico_mixture_template(mono.info, mz.tol = 0.5)

Arguments

mono.info

An output of gather_summary.

mz.tol

A m/z tolerance in Da. (Default: 0.5)

Value

A data frame which contains simulated m/z, log intensity, and normalized intensity values of peaks.

Examples

spectra.processed.A <- process_monospectra(
   file=system.file("extdata", "listA.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.B <- process_monospectra(
   file=system.file("extdata", "listB.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.C <- process_monospectra(
   file=system.file("extdata", "listC.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.mono.summary.A <- summarize_monospectra(
   processed.obj=spectra.processed.A,
   species='A', directory=tempdir())
spectra.mono.summary.B <- summarize_monospectra(
   processed.obj=spectra.processed.B,
   species='B', directory=tempdir())
spectra.mono.summary.C <- summarize_monospectra(
   processed.obj=spectra.processed.C,
   species='C', directory=tempdir())
mono.info=gather_summary(c(spectra.mono.summary.A, spectra.mono.summary.B, spectra.mono.summary.C))
template <- create_insilico_mixture_template(mono.info)

filtermass

Description

Internal function. This function removes peaks with their mass values (m/z values) outside a given mass range. This function is used in process_monospectra.

Usage

filtermass(spectra, mass.range)

Arguments

spectra

Mass Spectra (A MALDIquant MassSpectrum (S4) object). An output of importMzXml.

mass.range

Mass (m/z) range (a vector). For exmaple, c(1000,2200).

Value

A list of filtered mass spectra (MALDIquant MassSpectrum (S4) objects) which contains mass, intensity, and metaData.

gather_summary

Description

This function combines outputs from summarize_monospectra.

Usage

gather_summary(x)

Arguments

x

A list of multiple monomicrobial mass spectra information from summarize_monospectra.

Value

A list of combined summaries (data frames) of mass spectra from summarize_monospectra and the corresponding species (a vector).

Examples

spectra.processed.A <- process_monospectra(
   file=system.file("extdata", "listA.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.B <- process_monospectra(
   file=system.file("extdata", "listB.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.C <- process_monospectra(
   file=system.file("extdata", "listC.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.mono.summary.A <- summarize_monospectra(
   processed.obj=spectra.processed.A,
   species='A', directory=tempdir())
spectra.mono.summary.B <- summarize_monospectra(
   processed.obj=spectra.processed.B,
   species='B', directory=tempdir())
spectra.mono.summary.C <- summarize_monospectra(
   processed.obj=spectra.processed.C,
   species='C', directory=tempdir())
mono.info=gather_summary(c(spectra.mono.summary.A, spectra.mono.summary.B, spectra.mono.summary.C))

gather_summary_file

Description

This function combines output files from summarize_monospectra.

Usage

gather_summary_file(directory)

Arguments

directory

A directory that contains summary files from summarize_monospectra.

Value

A list of combined summaries of mass spectra (data frames) from summarize_monospectra and the corresponding species (a vector).

Examples

spectra.processed.A <- process_monospectra(
   file=system.file("extdata", "listA.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.B <- process_monospectra(
   file=system.file("extdata", "listB.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.C <- process_monospectra(
   file=system.file("extdata", "listC.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.mono.summary.A <- summarize_monospectra(
   processed.obj=spectra.processed.A,
   species='A', directory=tempdir())
spectra.mono.summary.B <- summarize_monospectra(
   processed.obj=spectra.processed.B,
   species='B', directory=tempdir())
spectra.mono.summary.C <- summarize_monospectra(
   processed.obj=spectra.processed.C,
   species='C', directory=tempdir())
summary <- gather_summary_file(directory=tempdir())

preprocessMS

Description

Internal function. This function preprocesses spectra by transforming/smoothing intensity, removing baseline, and calibrating intensities.

Usage

preprocessMS(spectra, halfWindowSize = 20, SNIP.iteration = 60)

Arguments

spectra

Spectra. A MALDIquant object. An output of either importMzXml or filtermass.

halfWindowSize

halfWindowSize The highest peaks in the given window (+/-halfWindowSize) will be recognized as peaks. (Default: 20). See detectPeaks for details.

SNIP.iteration

SNIP.iteration An iteration used to remove the baseline of an spectrum. (Default: 60). See removeBaseline for details.

Value

The processed mass spectra. A list of MALDIquant MassSpectrum objects (S4 objects).

process_monospectra

Description

This function processes multiple mzXML files which are listed in the file that an user specifies.

Usage

process_monospectra(
  file,
  mass.range = c(1000, 2200),
  halfWindowSize = 20,
  SNIP.iteration = 60
)

Arguments

file

A file name. This file is a tab-delimited file which contains the following columns: file names, strain.no, and strain. See below for details.

mass.range

The m/z range that users want to consider for the analysis. (Default: c(1000,2200)).

halfWindowSize

A half window size used for the smoothing the intensity values. (Default: 20). See smoothIntensity for details.

SNIP.iteration

An iteration used to remove the baseline of an spectrum. (Default: 60). See removeBaseline for details.

Value

A list of processed monobacterial mass spectra (S4 objects, MALDIquant MassSpectrum objects), and their strain numbers (a vector), unique strains (a vector), and strain names (a vector).

Examples

spectra.processed.A <- process_monospectra(
   file=system.file("extdata", "listA.txt", package="MGMS2"),
   mass.range=c(1000,2200))

simulate_ind_spec_single

Description

Internal function. The function simulates m/z and intensity values using given summary statistics.

Usage

simulate_ind_spec_single(interest, mz.tol, species, strain)

Arguments

interest

Summary statistics of spectra.

mz.tol

The tolerance of m/z. This is used to generate m/z values of peaks.

species

Species.

strain

Strain name.

Value

A data frame that contains m/z, (normalized) intensity values, missing rates of peaks, species name, and strain name.

simulate_many_poly_spectra

Description

The function creates simulated mass spectra in pdf file and returns simulated mass spectra (m/z and intensity values of peaks).

Usage

simulate_many_poly_spectra(
  mono.info,
  nsim = 10000,
  file = NULL,
  mixture.ratio,
  mixture.missing.prob.peak = 0.05,
  noise.peak.ratio = 0.05,
  snr.basepeak = 500,
  noise.cv = 0.25,
  mz.range = c(1000, 2200),
  mz.tol = 0.5
)

Arguments

mono.info

A list output of gather_summary or gather_summary_file.

nsim

The number of simulated spectra. (Default: 10000)

file

An output file name. (By default, file=NULL. No pdf file will be generated.)

mixture.ratio

A list of bacterial mixture ratios for given bacterial species in sim.template.

mixture.missing.prob.peak

A real value. The missing probability caused by mixing multiple bacteria species. (Default: 0.05)

noise.peak.ratio

A ratio between the numbers of noise and signal peaks. (Default: 0.05)

snr.basepeak

A (base peak) signal to noise ratio. (Default: 5000)

noise.cv

A coefficient of variation of noise peaks. (Default: 0.25)

mz.range

A range of m/z values. (Default: c(1000,2200))

mz.tol

m/z tolerance. (Default: 0.5)

Value

A list of data frames. A list of simulated mass spectra (data frames) that contains m/z values of peaks, normalized intensities of peaks, species names, and strain names. This function also creates pdf files which contain simulated spectra.

Examples

spectra.processed.A <- process_monospectra(
   file=system.file("extdata", "listA.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.B <- process_monospectra(
   file=system.file("extdata", "listB.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.C <- process_monospectra(
   file=system.file("extdata", "listC.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.mono.summary.A <- summarize_monospectra(
   processed.obj=spectra.processed.A,
   species='A', directory=tempdir())
spectra.mono.summary.B <- summarize_monospectra(
   processed.obj=spectra.processed.B,
   species='B', directory=tempdir())
spectra.mono.summary.C <- summarize_monospectra(
   processed.obj=spectra.processed.C,
   species='C', directory=tempdir())
mono.info=gather_summary(c(spectra.mono.summary.A, spectra.mono.summary.B, spectra.mono.summary.C))
mixture.ratio <- list()
mixture.ratio['A']=1
mixture.ratio['B']=0.5
mixture.ratio['C']=0
insilico.spectra <- simulate_many_poly_spectra(mono.info, mixture.ratio=mixture.ratio, nsim=10)

simulate_poly_spectra

Description

This function takes simulated m/z and intensities of peaks from create_insilico_mixture_template and modifies them based on given parameters.

Usage

simulate_poly_spectra(
  sim.template,
  mixture.ratio,
  spectrum.name = "Spectrum",
  mixture.missing.prob.peak = 0.05,
  noise.peak.ratio = 0.05,
  snr.basepeak = 500,
  noise.cv = 0.25,
  mz.range = c(1000, 2200)
)

Arguments

sim.template

A data frame which contains m/z, log intensitiy, normalized intensity values and missing rates of peaks. There are also species and strain information. An object of create_insilico_mixture_template.

mixture.ratio

A list of bacterial mixture ratios for given bacterial species in sim.template.

spectrum.name

A character. An user can define the spectrum name. (Default: 'Spectrum').

mixture.missing.prob.peak

A real value. The missing probability caused by mixing multiple bacteria species. (Default: 0.05)

noise.peak.ratio

A ratio between the numbers of noise and signal peaks. (Default: 0.05)

snr.basepeak

A (base peak) signal to noise ratio. (Default: 500)

noise.cv

A coefficient of variation of noise peaks. (Default: 0.25)

mz.range

A range of m/z values. (Default: c(1000,2200))

Value

A data frame that contains m/z values of peaks, normalized intensities of peaks, species names, and strain names. A modified version of sim.template.

Examples

spectra.processed.A <- process_monospectra(
   file=system.file("extdata", "listA.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.B <- process_monospectra(
   file=system.file("extdata", "listB.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.processed.C <- process_monospectra(
   file=system.file("extdata", "listC.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.mono.summary.A <- summarize_monospectra(
   processed.obj=spectra.processed.A,
   species='A', directory=tempdir())
spectra.mono.summary.B <- summarize_monospectra(
   processed.obj=spectra.processed.B,
   species='B', directory=tempdir())
spectra.mono.summary.C <- summarize_monospectra(
   processed.obj=spectra.processed.C,
   species='C', directory=tempdir())
mono.info=gather_summary(c(spectra.mono.summary.A, spectra.mono.summary.B, spectra.mono.summary.C))
mixture.ratio <- list()
mixture.ratio['A']=1
mixture.ratio['B']=0.5
mixture.ratio['C']=0
sim.template <- create_insilico_mixture_template(mono.info)
insilico.spectrum <- simulate_poly_spectra(sim.template, mixture.ratio)

summarize_monospectra

Description

This function summarizes monomicrobial spectra and writes summary in the specified directory.

Usage

summarize_monospectra(
  processed.obj,
  species,
  directory = NULL,
  minFrequency = 0.5,
  align.tolerance = 5e-04,
  snr = 3,
  halfWindowSize = 20,
  top.N = 50
)

Arguments

processed.obj

A list from process_monospectra which contains peaks information for each strain.

species

Species name.

directory

Directory. (By default, no summary file will be generated.)

minFrequency

Percentage value. A minimum occurrence proportion required for building a reference peaks. All peaks with their occurence proportion less than minFrequency will be moved. (Default: 0.50). See filterPeaks and referencePeaks for details.

align.tolerance

Mass tolerance. Must be multiplied by 10^-6 for ppm. (Default: 0.0005).

snr

Signal-to-noise ratio. (Default: 3).

halfWindowSize

The highest peaks in the given window (+/-halfWindowSize) will be recognized as peaks. (Default: 20). See detectPeaks for details.

top.N

The top N peaks will be chosen for the analysis. An integer value. (Default: 50).

Value

A data frame that contains the peaks informations: m/z, mean log intensity, standard deviation of log intensity, missing rate of peaks. In addition, it also contains species and strain information.

Examples

spectra.processed.A <- process_monospectra(
   file=system.file("extdata", "listA.txt", package="MGMS2"),
   mass.range=c(1000,2200))
spectra.mono.summary.A <- summarize_monospectra(
   processed.obj=spectra.processed.A, species='A',
   directory=tempdir())

summary_mono

Description

Internal function. This function calculates summary statistics for peaks afterling aligning spectra of interest.

Usage

summary_mono(
  spectra.interest,
  minFrequency = 0.5,
  align.tolerance = 5e-04,
  snr = 3,
  halfWindowSize = 20,
  top.N = 50
)

Arguments

spectra.interest

A list which contains peaks information for a strain of interest.

minFrequency

Percentage value. A minimum occurrence proportion required for building a reference peaks. All peaks with their occurence proportion less than minFrequency will be moved. (Default: 0.50). See filterPeaks and referencePeaks for details.

align.tolerance

Mass tolerance. Must be multiplied by 10^-6 for ppm. (Default: 0.0005).

snr

Signal-to-noise ratio. (Default: 3).

halfWindowSize

The highest peaks in the given window (+/-halfWindowSize) will be recognized as peaks. (Default: 20). See detectPeaks for details.

top.N

The top N peaks will be chosen for the analysis. An integer value. (Default: 50).

Value

Summary information (Data frame) of spectra of interest.